Seagen Beneish M-Score Historical Data
The historical data trend for Seagen's Beneish M-Score can be seen below:
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
Seagen Beneish M-Score Chart
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Seagen Annual Data
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Trend |
Dec13 |
Dec14 |
Dec15 |
Dec16 |
Dec17 |
Dec18 |
Dec19 |
Dec20 |
Dec21 |
Dec22 |
| Beneish M-Score |
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-1.42 |
-2.26 |
-1.86 |
-2.50 |
-2.61 |
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Seagen Quarterly Data
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Dec18 |
Mar19 |
Jun19 |
Sep19 |
Dec19 |
Mar20 |
Jun20 |
Sep20 |
Dec20 |
Mar21 |
Jun21 |
Sep21 |
Dec21 |
Mar22 |
Jun22 |
Sep22 |
Dec22 |
Mar23 |
Jun23 |
Sep23 |
| Beneish M-Score |
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-2.23 |
-2.61 |
-2.75 |
-2.67 |
-2.75 |
Competitive Comparison of Seagen's Beneish M-Score
For the Biotechnology subindustry, Seagen's Beneish M-Score, along with its competitors' market caps and Beneish M-Score data, can be viewed below:
* Competitive companies are chosen from companies within the same industry, with headquarter located in same country, with closest market capitalization; x-axis shows the market cap, and y-axis shows the term value; the bigger the dot, the larger the market cap. Note that "N/A" values will not show up in the chart.
Seagen's Beneish M-Score Distribution in the Biotechnology Industry
For the Biotechnology industry and Healthcare sector, Seagen's Beneish M-Score distribution charts can be found below:
* The bar in red indicates where Seagen's Beneish M-Score falls into.
Seagen Beneish M-Score Calculation
The M-score was created by Professor Messod Beneish. Instead of measuring the bankruptcy risk (Altman Z-Score) or business trend (Piotroski F-Score), M-score can be used to detect the risk of earnings manipulation. This is the original research paper on M-score.
The M-Score Variables:
The M-score of Seagen for today is based on a combination of the following eight different indices:
| M | = | -4.84 | + | 0.92 * DSRI | + | 0.528 * GMI | + | 0.404 * AQI | + | 0.892 * SGI | + | 0.115 * DEPI |
| = | -4.84 | + | 0.92 * 1.0514 | + | 0.528 * 1.0499 | + | 0.404 * 1.0219 | + | 0.892 * 1.234 | + | 0.115 * 1.5017 |
| - | 0.172 * SGAI | + | 4.679 * TATA | - | 0.327 * LVGI |
| - | 0.172 * 0.9557 | + | 4.679 * -0.072012 | - | 0.327 * 1.3767 |
| = | -2.58 |
* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.
| This Year (Sep23) TTM: | Last Year (Sep22) TTM: |
Total Receivables was $632 Mil.
Revenue was 648.65 + 603.832 + 519.719 + 528.15 = $2,300 Mil.
Gross Profit was 483.396 + 423.079 + 407.943 + 419.94 = $1,734 Mil.
Total Current Assets was $2,552 Mil.
Total Assets was $3,634 Mil.
Property, Plant and Equipment(Net PPE) was $488 Mil.
Depreciation, Depletion and Amortization(DDA) was $87 Mil.
Selling, General, & Admin. Expense(SGA) was $962 Mil.
Total Current Liabilities was $955 Mil.
Long-Term Debt & Capital Lease Obligation was $113 Mil.
Net Income was -215.789 + -211.528 + -174.737 + -148.171 = $-750 Mil.
Non Operating Income was 14.978 + 12.084 + 14.4 + 10.176 = $52 Mil.
Cash Flow from Operations was -35.823 + -175.245 + -249.643 + -79.44 = $-540 Mil.
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Total Receivables was $487 Mil.
Revenue was 510.3 + 497.502 + 426.46 + 429.851 = $1,864 Mil.
Gross Profit was 402.178 + 391.402 + 338.834 + 343.161 = $1,476 Mil.
Total Current Assets was $2,760 Mil.
Total Assets was $3,619 Mil.
Property, Plant and Equipment(Net PPE) was $280 Mil.
Depreciation, Depletion and Amortization(DDA) was $83 Mil.
Selling, General, & Admin. Expense(SGA) was $816 Mil.
Total Current Liabilities was $726 Mil.
Long-Term Debt & Capital Lease Obligation was $47 Mil.
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1. DSRI = Days Sales in Receivables Index
Measured as the ratio of Revenue in Total Receivables in year t to year t-1.
A large increase in DSR could be indicative of revenue inflation.
| DSRI | = | (Receivables_t / Revenue_t) | / | (Receivables_t-1 / Revenue_t-1) |
| = | (631.555 / 2300.351) | / | (486.755 / 1864.113) |
| = | 0.274547 | / | 0.261119 |
| | = | 1.0514 |
2. GMI = Gross Margin Index
Measured as the ratio of gross margin in year t-1 to gross margin in year t.
Gross margin has deteriorated when this index is above 1. A firm with poorer prospects is more likely to manipulate earnings.
| GMI | = | GrossMargin_t-1 | / | GrossMargin_t |
| = | (GrossProfit_t-1 / Revenue_t-1) | / | (GrossProfit_t / Revenue_t) |
| = | (1475.575 / 1864.113) | / | (1734.358 / 2300.351) |
| = | 0.79157 | / | 0.753954 |
| | = | 1.0499 |
3. AQI = Asset Quality Index
AQI is the ratio of asset quality in year t to year t-1.
Asset quality is measured as the ratio of non-current assets other than Property, Plant and Equipment to Total Assets.
| AQI | = | (1 - (CurrentAssets_t + PPE_t) / TotalAssets_t) | / | (1 - (CurrentAssets_t-1 + PPE_t-1) / TotalAssets_t-1) |
| = | (1 - (2551.593 + 487.662) / 3634.261) | / | (1 - (2759.619 + 279.61) / 3619.078) |
| = | 0.163721 | / | 0.16022 |
| | = | 1.0219 |
4. SGI = Sales Growth Index
Ratio of Revenue in year t to sales in year t-1.
Sales growth is not itself a measure of manipulation. However, growth companies are likely to find themselves under pressure to manipulate in order to keep up appearances.
| SGI | = | Sales_t | / | Sales_t-1 |
| = | Revenue_t | / | Revenue_t-1 |
| = | 2300.351 | / | 1864.113 |
| | = | 1.234 |
5. DEPI = Depreciation Index
Measured as the ratio of the rate of Depreciation, Depletion and Amortization in year t-1 to the corresponding rate in year t.
DEPI greater than 1 indicates that assets are being depreciated at a slower rate. This suggests that the firm might be revising useful asset life assumptions upwards, or adopting a new method that is income friendly.
| DEPI | = | (Depreciation_t-1 / (Depreciaton_t-1 + PPE_t-1)) | / | (Depreciation_t / (Depreciaton_t + PPE_t)) |
| = | (82.765 / (82.765 + 279.61)) | / | (87.47 / (87.47 + 487.662)) |
| = | 0.228396 | / | 0.152087 |
| | = | 1.5017 |
Note: If the Depreciation, Depletion and Amortization data is not available, we assume that the depreciation rate is constant and set the Depreciation Index to 1.
6. SGAI = Sales, General and Administrative expenses Index
The ratio of Selling, General, & Admin. Expense(SGA) to Sales in year t relative to year t-1.
SGA expenses index > 1 means that the company is becoming less efficient in generate sales.
| SGAI | = | (SGA_t / Sales_t) | / | (SGA_t-1 /Sales_t-1) |
| = | (962.161 / 2300.351) | / | (815.799 / 1864.113) |
| = | 0.418267 | / | 0.437634 |
| | = | 0.9557 |
7. LVGI = Leverage Index
The ratio of total debt to Total Assets in year t relative to yeat t-1.
An LVGI > 1 indicates an increase in leverage
| LVGI | = | ((LTD_t + CurrentLiabilities_t) / TotalAssets_t) | / | ((LTD_t-1 + CurrentLiabilities_t-1) / TotalAssets_t-1) |
| = | ((113.487 + 954.716) / 3634.261) | / | ((46.703 + 725.998) / 3619.078) |
| = | 0.293926 | / | 0.213508 |
| | = | 1.3767 |
8. TATA = Total Accruals to Total Assets
Total accruals calculated as the change in working capital accounts other than cash less depreciation.
| TATA | = | (IncomefromContinuingOperations_t | - | CashFlowsfromOperations_t) | / | TotalAssets_t |
| = | (NetIncome_t - NonOperatingIncome_t | - | CashFlowsfromOperations_t) | / | TotalAssets_t |
| = | (-750.225 - 51.638 | - | -540.151) | / | 3634.261 |
| | = | -0.072012 |
An M-Score of equal or less than -1.78 suggests that the company is unlikely to be a manipulator. An M-Score of greater than -1.78 signals that the company is likely to be a manipulator.
Seagen has a M-score of -2.58 suggests that the company is unlikely to be a manipulator.
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